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I'm an applied math nerd interested in higher categorical applications in sensor fusion and tomography.

• 📚 I'm currently working through:
  • Topological Signal Processing
  • Categories for the Working Mathematician
  • Sheaves in Geometry and Logic: A First Introduction to Topos Theory
  • The Stacks Project (Obviously not all of it, that would be insane 💀)
• 🌱 I'm working on some fun side projects in Rust like these
  • type_sheaf
  • bloch
• 🖥️ I work mainly in Rust, Python, SQL, and Julia

BSc - Mathematical Physics, University of Waterloo (ongoing)

In my past life, I led research on decentralized portfolio management at Primitive. My focus was primarily on exploring applications of dynamically-adjusted CFMMs (of which we called DFMMs) in structured product design and trust-less on-chain portfolio management. I particularly was focused on institutional/treasury management use cases, as they are the exact class of consumers in need of this passificity and trustless design. There are still plenty of open questions in this area that interest me, so I'm always open to people shooting me a DM with other cool problems in this area! You can find some of my writings on portfolio management below:

• 🥛 Introduction to On-Chain Portfolio Management
  • Your liquidity distribution is your portfolio gamma as a CFMM liquidity provider.
• 🍪 Portfolio Management: Fee Generation in AMMs
  • The path dependence of fee generation drives the necessity for dynamically-adjusted CFMMs.
• 🕹️ Financial Virtual Machine - Feb 2023
  • Primitive Yellowpaper. The Financial Virtual Machine (FVM) is designed to be a general purpose Finite State Machine (FSM), built on top of the EVM, that can be used to interact with a variety of structured financial products.
• 📈 Replicating Portfolios: Constructing Permissionless Derivatives - May 2022
  • Example reconstructions of traditional structured products built around RMM-01. Concludes CFMMs are invaluable for structured product design with minimized trust dependencies.
• 🏛️ Primitive RMM-01 - Oct 2021
  • Primitive Original Whitepaper. An implementation of an CFMM that approximates a Black–Scholes covered call, which we called RMM-01.